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caret (version 5.05.004)
Classification and Regression Training
Description
Misc functions for training and plotting classification and regression models
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Install
install.packages('caret')
Monthly Downloads
230,598
Version
5.05.004
License
GPL-2
Maintainer
Max Kuhn
Last Published
October 11th, 2011
Functions in caret (5.05.004)
Search all functions
BloodBrain
Blood Brain Barrier Data
aucRoc
Compute the area under an ROC curve
bag.default
A General Framework For Bagging
caret-internal
Internal Functions
bagFDA
Bagged FDA
bagEarth
Bagged Earth
cars
Kelly Blue Book resale data for 2005 model year GM cars
avNNet.default
Neural Networks Using Model Averaging
classDist
Compute and predict the distances to class centroids
BoxCoxTrans.default
Box-Cox Transformations
confusionMatrix
Create a confusion matrix
diff.resamples
Inferential Assessments About Model Performance
cox2
COX-2 Activity Data
confusionMatrix.train
Estimate a Resampled Confusion Matrix
GermanCredit
German Credit Data
dhfr
Dihydrofolate Reductase Inhibitors Data
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
dotPlot
Create a dotplot of variable importance values
filterVarImp
Calculation of filter-based variable importance
findCorrelation
Determine highly correlated variables
findLinearCombos
Determine linear combinations in a matrix
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
format.bagEarth
Format 'bagEarth' objects
knn3
k-Nearest Neighbour Classification
icr.formula
Independent Component Regression
predict.train
Extract predictions and class probabilities from train objects
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
knnreg
k-Nearest Neighbour Regression
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
modelLookup
Descriptions Of Models Available in train()
dummyVars
Create A Full Set of Dummy Variables
nearZeroVar
Identification of near zero variance predictors
oil
Fatty acid composition of commercial oils
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
nullModel
Fit a simple, non-informative model
maxDissim
Maximum Dissimilarity Sampling
panel.needle
Needle Plot Lattice Panel
plot.varImp.train
Plotting variable importance measures
createGrid
Tuning Parameter Grid
plot.train
Plot Method for the train Class
pcaNNet.default
Neural Networks with a Principal Component Step
plotClassProbs
Plot Predicted Probabilities in Classification Models
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
pottery
Pottery from Pre-Classical Sites in Italy
histogram.train
Lattice functions for plotting resampling results
postResample
Calculates performance across resamples
lift
Lift Plot
predictors
List predictors used in the model
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
prcomp.resamples
Principal Components Analysis of Resampling Results
preProcess
Pre-Processing of Predictors
predict.knn3
Predictions from k-Nearest Neighbors
predict.bagEarth
Predicted values based on bagged Earth and FDA models
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
resampleHist
Plot the resampling distribution of the model statistics
print.train
Print Method for the train Class
resampleSummary
Summary of resampled performance estimates
print.confusionMatrix
Print method for confusionMatrix
rfeControl
Controlling the Feature Selection Algorithms
roc
Compute the points for an ROC curve
rfe
Backwards Feature Selection
caretFuncs
Backwards Feature Selection Helper Functions
caretSBF
Selection By Filtering (SBF) Helper Functions
sbfControl
Control Object for Selection By Filtering (SBF)
sbf
Selection By Filtering (SBF)
segmentationData
Cell Body Segmentation
oneSE
Selecting tuning Parameters
sensitivity
Calculate sensitivity, specificity and predictive values
spatialSign
Compute the multivariate spatial sign
tecator
Fat, Water and Protein Content of Meat Samples
trainControl
Control parameters for train
varImp
Calculation of variable importance for regression and classification models
resamples
Collation and Visualization of Resampling Results
summary.bagEarth
Summarize a bagged earth or FDA fit
as.table.confusionMatrix
Save Confusion Table Results
train
Fit Predictive Models over Different Tuning Parameters
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
panel.lift2
Lattice Panel Functions for Lift Plots
createDataPartition
Data Splitting functions